ارزیابی مدل همانند‌سازی و پیش‌بینی عملکرد دانة گیاه لوبیاچیتی (Phaseolus vulgaris L.)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 مربی، مرکز ملی ذخایر ژنتیکی و زیستی ایران (IBRC)، جهاد دانشگاهی (ACECR)

2 استادیار، گروه زراعت، دانشگاه علوم کشاورزی و منابع طبیعی گرگان

3 کارشناس، تولیدات گیاهی، بانک گیاهی مرکز ملی ذخایر ژنتیکی و زیستی ایران، جهاد دانشگاهی (ACECR)

چکیده

در این پژوهش، برای همانند­سازی و پیش­بینی عملکرد گیاه لوبیاچیتی در شهرستان خمین با استفاده از مدل، تغییرات روزانه مربوط به گذارشناسی (فنولوژی)، مادة خشک، سطح برگ و موازنة آب خاک، از طریق آمار روزانة هواشناسی (دمای کمینه و بیشینه، میزان تابش و بارندگی) و با استفاده از داده­های استانی و داده­های دیگر پژوهشگران در نقاط مختلف جهان، محاسبه شد و عملکرد در پایان فصل پیش­بینی شد. عملکرد مشاهده‌شده دامنة تغییرپذیری 2518 تا 3066 کیلوگرم در هکتار داشت و با میانگین 2832 کیلوگرم در هکتار بود؛ درحالی‌که دامنة تغییرپذیری عملکرد پیش‌بینی‌شده 2260 تا 2780 کیلوگرم در هکتار و میانگین 2643 کیلوگرم در هکتار داشت. مقدار R2، ضریب تغییرپذیری (CV) و جذر میانگین مربعات انحرافات (RMSD) مدل به ترتیب 83 درصد، 6/1 درصد و 205 کیلوگرم در هکتار بود. بنابراین استنباط می­شود که این مدل می­تواند برای پیش­بینی رشد و عملکرد لوبیا در شرایط شهرستان خمین دقت مناسبی داشته باشد. همچنین این امکان وجود دارد تا در صورت فراهم بودن داده­های مربوط به زیرمدل­های نام‌برده و نیز نتایج به‌دست‌آمده از داده­های منطقه­ای مربوط به تراکم و تاریخ­های کشت دیگر گیاهان بذر محصول، بتوان از این مدل، برای همانند­سازی و پیش­بینی رشد و عملکرد آن‌ها استفاده کرد.

کلیدواژه‌ها


عنوان مقاله [English]

Evaluating the simulate and prediction model of chitti bean (Phaseolus vulgaris L.) grain yield

نویسندگان [English]

  • Elyas Aryakia 1
  • Benjamin Torabi 2
  • Azita Aryakia 3
1 Instructor, Plant bank, Horticultural Sciences, Iranian Biological Resource Center (IBRC), Academic Center for Education, Culture and Research (ACECR), I.R. Iran
2 Assistant Professor, Department of Agronomy, Gorgan university of Agricultural Sciences and Natural Resources, Iran
3 Expert, Plant bank, Plant production, Iranian Biological Resource Center (IBRC), Academic Center for Education, Culture and Research (ACECR), I.R. Iran
چکیده [English]

In this study, for simulation and prediction the yield of chitti bean, it is necessary to assess sub models include of phenology, production and dry matter distribution, leaf area changes and equilibrium of water-soil. The sub model parameters were estimated by using information of date plantings, different plant densities and different years at khomein Research Station and data results of Scientists around the world. Using this model, daily changes of sub models were calculated based on daily meteorological statistics (minimum temperature, maximum temperature, radiation and rain) and finally the yield was predicted. The resulting range of observed yield was 2518 to 3066 kg.h-1 with average of 2832 kg.h-1; whereas the resulting range of predicted yield was 2260 to 2870 kg.h-1 with average of 2643 kg.h-1. R2, CV and RMSD were %83, %1.6 and 205 kg.h-1, respectively. Therefore, it can be concluded that this model have appropriate accuracy for prediction of the growth and yield of common bean in khomein. Also it is possible to predict growth and yield responses of other crops if the data of sub models and regional data results of density and planting date of seed crops are available.

کلیدواژه‌ها [English]

  • Bean
  • Model
  • Phenology
  • simulation
  • yield
  1. Alimadadi, A., Jahansooz, M. R., Ahmadi, A., Tavakol, R. & Rostamza, M. (2006). Cowpea, common bean and mung bean radiation use efficiency, light extinction coefficient and radiation interception in double cropping. Pajouhesh- Va- Sazandegi, 71, 67-75. (in Farsi)
  2. Amini, R., Alizadeh, H. & Yousefi, A. R. (2014). Interference between red kidneybean (Phaseolusvulgaris L.) cultivarsand redroot pigweed (Amaranthus retroflexus L.). Europian Journal of Agronomy, 60, 13-21.
  3. Anonymous. (2008). FAO. Statistics of Agriculture Crops in the World. ttp://www.fao.org.
  4. Anonymous. (2009). Statistics of Agricultural Crops. Center of Statistics and Information, Ministry of Jihad-e-Agriculture, Tehran, Iran (in Persian).
  5. Bayat, A. A., Sepehri, A., Ahmadvand, G. & Dorri, H. R. (2010). Effect of water deficit stress on yield and yield components of pinto bean (Phaseolus vulgaris L.) genotypes. Iranian Journal of Crop Sciences, 12(1), 42-54. (in Farsi)
  6. Behboudi, F., Allahdadi, E. & Mohamadi, E. (2013).The effect of vermicompost containing copper oxide (CuO) and zinc oxide (ZnO) nanoparticles on some characteristics of the wax bean. Electronic Journal of Crop Production, 6(2), 33-49. (in Farsi)
  7. Bouman, B. A. M., Van Keulen, H., Van Laar, H. H. & Rabbinge, R. (1996). The School of de Wit crop growth simulation models: pedigree and historical overview. Agricultural Systems, 52(2/3), 171-198.
  8. Confalon, A., Lizaso, J., Ruiz-nogueira, B., Lopez-cedron, F. X. & Sau, F. (2010). Growth, par use efficiency, and yield components of field-grown vicia faba under different temperature and photoperiod regimes. Field Crop Research, 115, 140-148.
  9. Coulson, C. L. (1985). Radiant energy conversion in three cultivars of Phaseolus vulgaris. Agricultural and Forest Meteorology, 35(1-4), 21-29.
  10. De Wit, C. T. (1965). Photosyntesis of lesf canopies. Agriculture Research Reports. PUDOC, Wageningen, Netherlands.
  11. Egli, D. B. (1998). Seed biology and the yield of grain crops. CAB International, Wallingford, UK.
  12. Fageria, N. K. (1992). Maximizing Crop Yields. CRC Press.
  13. Ferreira, M. E., Abreu, J. P. de M., Bianco, V. V. & Monteiro, A. (1997). Predicting phasic development of green beans for processing using a model with high temperature reduction of thermal time accumulation. Scientia Horticulturae, 69(3/4), 123-133.
  14. Ghadiri, H.  & Bayat, M. L. (2004). Effect of Row and Plant Spacings on Weed Competition with Pinto Beans (Phaseolus vulgaris L.). Journal of Agriculture Science and Technology, 6, 1-9.
  15. Ghanbari, A. & Taheri mazandarani, M. (2003). Effects of sowing date and plant density on yield of spotted bean. Seed and Plant Improvement Journal, 19(4), 483-496. (in Farsi)
  16. Hammer, G. L., Goyne, P. J. & Woodruff, D. R. (1982). Phenology of sunflower cultivars. III. Models for prediction in field environments. Australian Journal of Agricultural Research, 33, 263-274.
  17. Hoogenboom, G., White, J. W., Jones, J. W. & Boote, K. J. (1991). Dry bean crop growth simulation model user's guide. Florida Agricultural Experiment Station Journalno. N-00379, University of Florida, Gainesville.
  18. Jones, H. G. (1992). Plants and Microclimate, (2nd Edition). A quantitative approach to environmental plant physiology. Cambridge University Press, Cambridge. pp.428.
  19. Kamelmanesh, M. M., Namayande, A., Dori, H. R. & Bihamta, M. R. (2012). Effects of Bean common mosaic virus on Seed Yield, Yield Components and Phenological Phases of Common Bean (Phaseolus vulgaris L.) Under Field Conditions. Seed and Plant Improvement Journal, 28(1), 39-52. (in Farsi)
  20. Khaledian, M. R., Mailhol, J. C., Ruelle, P. & Rosique, P. (2009). Adapting PILOTE model for water and yield management under direct seeding system: the case of corn and durum wheat in a Mediterranean context. Agricultural Water Management, 96(5), 757-770.
  21. Kiniry, J. R. & Knievel, D. P. (1995). Response of maize seed number to solar radiation intercepted soon after anthesis. Agronomy Journal, 87, 228-234.
  22. Kiniry, J. R., Simpson, C. E., Schubert, A. M. & Reed, J. D. (2004). Peanut leaf area index, light interception, radiation use efficiency, and harvest index at three sites in Texas. Field Crops Research, 91, 297-306.
  23. Kiniry, J. R., Tischler, C. R. & Van Esbroeck, G. A. (1999). Radiation use efficiency and leaf C02 exchange for divers C4 grasses. Biomass and Bioenergy.17, 95-112.
  24. Lak, M. R., Ghanbari, A. A., Dorri, H. R. & Gahadiri, A. (2009). Effect of Planting Date on Seed Yield and Fusarium Root Rot Disease Severity in Chitti Bean in Khomein. Seed and Plant Production Journal, 25(3), 275-286. (in Farsi)
  25. Loomis, R. S. & Williams, W. A. (1963). Maximum crop productivity: an stimate. Crop Science, 3, 67-72.
  26. Mailhol, J. C., Olufayo, A. A. & Ruelle, P. (1997). Sorghum and sunflower evapotranspiration and yield from simulated leaf area index. Agricultural Water Management, 35, 167-182.
  27. Marcelis, L. F. M., Heuvelink, E. & Goudriaan, J. (1998). Modelling biomass production and yield of horticultural crops: A review. Scientia Horticulturae, 74(1), 83-111.
  28. Marrou, H., Sinclair, T. R. & Metral, R. (2014). Assessment of irrigation scenarios to improve performances of Lingotbean (Phaseolus vulgaris) in southwest France. European Journal of Agronomy, 59, 22-28.
  29. Meireles, E. J. L., Pereira, A. R., Sentelhas, P. S., Stone, L. F. & Zimmermann, F. G. P. (2002). Calibration and test of the cropgro-dry bean Model for edaphoclimatic conditions in the savanas of central Brazil. Scientia Agricola, 59(4), 723-729.
  30. O’Connell, M. G., O’Leary, G. J., Whitfield, D. M. & Connor, D. J. (2004). Interception of photosynthetically active radiation and radiation-use efficiency of wheat, field pea and mustard in a semi-arid environment. Field Crops Research, 85(2/3), 111-124.
  31. Oliveira, E. C., Costa, J. M. N., Paula Júnior, T. J., Ferreira, W. P. M., Justino, F. B. & Neves, L.O. · (2012). The performance of the CROPGRO model for bean (Phaseolusvulgaris L.) yield simulation.Acta Scientiarium, 34(3), 239-246.
  32. Pannkuk, C. D., Stockle, C. O. & Papendick, R. I. (1998). Evaluating CropSyst Simulations of Wheat Management in a Wheat-Fallow Region of the US Pacific Northwest. Agricultural Systems, 57(2), 121-134.
  33. Pengelly, B. C., Blamey, F. P. C. & Muchow, R. C. (1999). Radiation interception and the accumulation of biomass and nitrogen by soybean and three tropical annual forage legumes. Field Crops Research, 63(2), 99-112.
  34. Perry, M. W., Siddique, K. H. M. & Wallace, J. F. (1987). Predicting phonological development of Australian wheats. Australian Journal of Agricultural Research, 38, 809-819.
  35. Rezaei, A. & KamgarHaghighi, A. (2009). The effect of water stress at different growth stages on the yield of cowpeas. Journal of soil research (soil and water science), 23(1), 17-124. (in Farsi)
  36. Soghani, M., Vaezi, S. H. & Sabaghpour, S. H. (2010). Evaluation of morpho-physiological characteristics, grain yield and its components in common bean genotypes (Phaseolus vulgaris L.). Iranian Journal of Crop Sciences, 12 (4), 436-451. (in Farsi)
  37. Soltani, A. (2009). Mathematical Modeling in Field Crops. JDM Press. (in Farsi)
  38. Soltani, A. & Hoogenboom, G. (2007). Assessing crop management options with crop simulation models based on generated weather data. Field Crops Research, 103(3), 198-207.
  39. Soltani, A., Ghasemi, K., Rahimzad, F., Moghadam, M. & Mirnia, M. (1999). CICER: A computer model for simulation of growth, yield of cicer. Agricultural Knowledge journal, 89-106. (in Farsi)
  40. Soltani, A., Robertson, M. J., Rahemi-Karizaki, A., Pooreza, J. & Zarei, H. (2006). Modeling biomass accumulation and partitioning in chickpea (Cicer arietinum L.). Journal of Agronomy and Crop Science, 192, 379-389.
  41. Soltani, A., Robertson, M. J., Rahemi-Karizaki, A., Poorreza, J. & Zarei, H. (2006). Modeling Biomass accumulation and partitioning in chickpea (Cicer arietinum L.). Journal of Agronomy and Crop Science, 92, 379-389.
  42. Soltania, A. F., Zeynali, E. & Galeshi, S. A. (2000). A computer program for simulation of canopy photosynthesis and transpiration in crops. Journal of Agricultural Sciences and Natural Resources, 7(1), 35-44. (in Farsi)
  43. Tesfaye, K., Walker, S. & Tsubo, M. (2006). Radiation interception and radiation use efficiency of three grain legumes under water deficit conditions in a semi-arid environment European Journal of Agronomy, 25(1), 60-70.
  44. Torabi, B. & Soltani, A. (2013). A Simple Model for Predicting Grain Yield of Maize Single Cross Hybrid. Journal of Crop Production and Processing, 3(7), 47-59. (in Farsi)
  45. Tsubo, M., Walker, S. & Mukhala, E. (2001). Comparison of radiation uses efficiency of mono-/inter –cropping systems with different row orientations. Field Crop Research, 71(1), 17-29.
  46. Walker, S. & Ogindo, H. O. (2003). The water budget of rained maize and bean intercrop. Physics and Chemistry of the Earth, 28(20-27), 919-926.
  47. Watson, D. J. (1974). Comparative physiological studies on the growth of field crops: I. Variation in net assimilation rate and leaf area between species and varieties and within and between years. Annual Botany, 11, 41-46.
  48. Wien, H. C. (1982). Dry matter production, leaf area development and light interception of cowpea lines with broad and narrow leaflet shape. Crop Science, 22(4), 733-737.